OCTIS (Terragni et al., 2021a, Optimizing and. Comparing is Simple!) is an open-source evalu- ation framework for the comparison of topic mod- els, that allows ...
In this paper, we present OCTIS, a framework for training, analyzing, and comparing Topic Models, whose optimal hyper-parameters are estimated using a Bayesian ...
OCTIS is an open-source framework for training, evaluating and comparing Topic Models. This tool uses single-objective Bayesian Optimization (BO) to ...
MIND-Lab/OCTIS: OCTIS: Comparing Topic Models is Simple! A ... - GitHub
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OCTIS (Optimizing and Comparing Topic models Is Simple) aims at training, analyzing and comparing Topic Models, whose optimal hyperparameters are estimated ...
OCTIS is an open-source framework for training, evaluating and comparing Topic Models. This tool uses single-objective Bayesian Optimization (BO) to optimize ...
OCTIS 2.0: Optimizing and Comparing Topic Models in Italian Is Even Simpler! S. Terragni, and E. Fersini. CLiC-it, volume 3033 of CEUR Workshop Proceedings ...
OCTIS allows researchers and practitioners to have a fair comparison between topic models of interest, using several benchmark datasets and well-known ...
Missing: 2.0: Italian Even
OCTIS: Comparing and optimizing topic models is simple! S Terragni, E Fersini, BG Galuzzi, P Tropeano, A Candelieri. Proceedings of the 16th Conference of the ...
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What is Octis?
Apr 19, 2021 · In this paper, we present OCTIS, a framework for training, analyzing, and comparing Topic. Models, whose optimal hyper-parameters are.
Missing: 2.0: Even Simpler!
May 3, 2023 · Preprocess your own dataset or use one of the already-preprocessed benchmark datasets. • Well-known topic models (both classical and neurals).